Computational Science and Technology : 7th ICCST 2020, Pattaya, Thailand, 29–30 August, 2020 / edited by Rayner Alfred, Hiroyuki Iida, Haviluddin Haviluddin, Patricia Anthony

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Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Lecture Notes in Electrical Engineering ; 724Publisher: Singapore : Springer Singapore, 2021Publisher: Singapore : Imprint: Springer, 2021Edition: 1st ed. 2021Description: 1 Online-Ressource(XIII, 585 p. 221 illus., 146 illus. in color.)ISBN:

9789813340695

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Additional physical formats: 9789813340688 | 9789813340701 | 9789813340718 | Erscheint auch als: 9789813340688 Druck-Ausgabe | Erscheint auch als: 9789813340701 Druck-Ausgabe | Erscheint auch als: 9789813340718 Druck-AusgabeDOI: DOI: 10.1007/978-981-33-4069-5Online resources:

Summary: Building a Knowledge Graph of Vietnam Tourism from Text -- Technology Adoption Models: Users’ Online Social Media Behavior Towards Visual Information -- A Pedagogical Framework with Integration of TPACK for Mobile Interactive System in Teaching Mathematics -- Towards Palm Bunch Ripeness Classification using Colour and Canny Edge Detection -- Attention Models for Sentiment Analysis using Objectivity and Subjectivity Word Vectors -- A Question-Answering System that Can Count -- Contactless Patient Authentication for Registration Using Face Recognition Technology -- Drawing and Recognising Simple Shapes with Real-Time Feedback Using Pattern Recognition -- Information Technology Students' Preferences on Blended Learning -- Improved Facial Recognition Algorithms based on Dragonfly and Grasshopper Optimization.Summary: This book gathers the proceedings of the Seventh International Conference on Computational Science and Technology 2020 (ICCST 2020), held in Pattaya, Thailand, on 29–30 August 2020. The respective contributions offer practitioners and researchers a range of new computational techniques and solutions, identify emerging issues, and outline future research directions, while also showing them how to apply the latest large-scale, high-performance computational methods.PPN: PPN: 1753064392Package identifier: Produktsigel: ZDB-2-SCS | ZDB-2-SXCS | ZDB-2-SEB

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